Search

The SPATA5 gene encodes a 892 amino-acids long protein that has a putative mitochondrial targeting sequence and has been proposed to function in maintenance of mitochondrial function and integrity during mouse spermatogenesis. Several studies have associated homozygous or compound heterozygous mutations in SPATA5 gene to microcephaly, intellectual disability, seizures and hearing loss. This suggests a role of the SPATA5 gene also in neuronal development. Recently, our group presented results validating the use of blood cells for the assessment of mitochondrial function for diagnosis and follow-up of mitochondrial disease, minimizing the need for invasive procedures such as muscle biopsy. In this study, we were able to diagnose a patient with epileptogenic encephalopathy using next generation sequencing. We found two novel compound heterozygous variants in SPATA5 that are most likely causative. To analyze the impact of SPATA5 mutations on mitochondrial functional studies directly on the patients' mononuclear cells and platelets were undertaken. Oxygen consumption rates in platelets and PBMCs were impaired in the patient when compared to a healthy control. Also, a decrease in mitochondrial mass was observed in the patient monocytes with respect to the control. This suggests a true pathogenic effect of the mutations in mitochondrial function, especially in energy production and possibly biogenesis, leading to the observed phenotype., (© 2023. The Author(s).)

Background: Lissencephaly (LIS) is a cortical malformation, characterized by smooth or nearly smooth cerebral surface and a shortage of gyral and sulcal development, which is caused by deficient neuronal migration during embryogenesis. Neuronal migration involves many gene products, among which is the product of the PAFAH1B1 gene, associated with this disease. LIS is a rare disease, characterized by low population frequency, and with non-specific clinical symptoms such as early epilepsy, developmental delay or cerebral palsy-like motor problems. Given that high-throughput sequencing techniques have been improving diagnosis, we have chosen this technique for addressing this patient., Case Presentation: We present the case of a seven years old male patient with an undiagnosed rare disease, with non-specific clinical symptoms possibly compatible with lissencephaly. The patient was enrolled in a study that included the sequencing of his whole genome. Sequence data was analyzed following a bioinformatic pipeline. The variants obtained were annotated and then subjected to different filters for prioritization. Also mitochondrial genome was analyzed. A novel candidate frameshift insertion in known PAFAH1B1 gene was found, explaining the index case phenotype. The assessment through in silico tools reported that it causes nonsense mediated mechanisms and that it is damaging with high confidence scores. The insertion causes a change in the reading frame, and produces a premature stop codon, severely affecting the protein function and probably the silencing of one allele. The healthy mother did not carry the mutation, and the unaffected father was not available for analysis., Conclusions: Through this work we found a novel de novo mutation in LIS1/PAFAH1B1 gene, as a likely cause of a rare disease in a young boy with non-specific clinical symptoms. The mutation found correlates with the phenotype studied since the loss of function in the gene product has already been described in this condition. Since there are no other variants in the PAFAH1B1 gene with low population frequency and due to family history, a de novo disease mechanism is proposed., (© 2022. The Author(s).)

Background: Sleep disturbances are an underestimated risk factor for suicidal ideation and behavior. Previous research provided preliminary support of a temporal relationship between sleep disturbances and suicidal ideation. The present study therefore sought to investigate the prospective association between sleep disturbances, passive and active suicidal ideation, and further psychological risk factors, such as state impulsivity and depression., Methods: Seventy-three psychiatric inpatients (71% female) with unipolar depressive disorder and current or lifetime suicidal ideation took part in an ecological momentary assessment (EMA). Participants filled out a baseline assessment and data were collected via smartphones over a 6-days period. Multilevel analyses with sleep disturbance as predictor for active and passive suicidal ideation, state impulsivity, and depression were carried out., Results: Patients with sleep disturbance experienced more active suicidal ideation, but no passive suicidal ideation, the following day. Of the four state impulsivity items, one item was significantly associated with sleep disturbance. Sleep disturbance had no effect on next-day depression. Limiting factors are the small and homogeneous sample along with the rather short observation period in an inpatient setting., Conclusions: The micro-longitudinal study provides preliminary support for sleep disturbance as a proximal risk factor for next-day active suicidal ideation. Clinically, results indicate to consider the evaluation and treatment of sleep disturbances for an improved risk assessment and prevention of suicide., (© 2022. The Author(s).)

Background: Missing data is a common issue in different fields, such as electronics, image processing, medical records and genomics. They can limit or even bias the posterior analysis. The data collection process can lead to different distribution, frequency, and structure of missing data points. They can be classified into four categories: Structurally Missing Data (SMD), Missing Completely At Random (MCAR), Missing At Random (MAR) and Missing Not At Random (MNAR). For the three later, and in the context of genomic data (especially non-coding data), we will discuss six imputation approaches using 31,245 variants collected from ClinVar and annotated with 13 genome-wide features., Results: Random Forest and kNN algorithms showed the best performance in the evaluated dataset. Additionally, some features show robust imputation regardless of the algorithm (e.g. conservation scores phyloP7 and phyloP20), while other features show poor imputation across algorithms (e.g. PhasCons). We also developed an R package that helps to test which imputation method is the best for a particular data set., Conclusions: We found that Random Forest and kNN are the best imputation method for genomics data, including non-coding variants. Since Random Forest is computationally more challenging, kNN remains a more realistic approach. Future work on variant prioritization thru genomic screening tests could largely profit from this methodology., (© 2021. The Author(s).)

Background: Rare diseases are pathologies that affect less than 1 in 2000 people. They are difficult to diagnose due to their low frequency and their often highly heterogeneous symptoms. Rare diseases have in general a high impact on the quality of life and life expectancy of patients, which are in general children or young people. The advent of high-throughput sequencing techniques has improved diagnosis in several different areas, from pediatrics, achieving a diagnostic rate of 41% with whole genome sequencing (WGS) and 36% with whole exome sequencing, to neurology, achieving a diagnostic rate between 47 and 48.5% with WGS. This evidence has encouraged our group to pursue a molecular diagnosis using WGS for this and several other patients with rare diseases., Results: We used whole genome sequencing to achieve a molecular diagnosis of a 7-year-old girl with a severe panvascular artery disease that remained for several years undiagnosed. We found a frameshift variant in one copy and a large deletion involving two exons in the other copy of a gene called YY1AP1. This gene is related to Grange syndrome, a recessive rare disease, whose symptoms include stenosis or occlusion of multiple arteries, congenital heart defects, brachydactyly, syndactyly, bone fragility, and learning disabilities. Bioinformatic analyses propose these mutations as the most likely cause of the disease, according to its frequency, in silico predictors, conservation analyses, and effect on the protein product. Additionally, we confirmed one mutation in each parent, supporting a compound heterozygous status in the child., Conclusions: In general, we think that this finding can contribute to the use of whole genome sequencing as a diagnosis tool of rare diseases, and in particular, it can enhance the set of known mutations associated with different diseases.

Background: Some multifunctional cellular proteins, as the monocyte chemotactic protein-induced protein 1 (ZC3H12A/MCPIP1) and the cyclin-dependent kinase inhibitor CDKN1A/p21, are able to modulate the cellular susceptibility to the human immunodeficiency virus type 1 (HIV-1). Several studies showed that CDKN1A/p21 is expressed at high levels ex vivo in cells from individuals who naturally control HIV-1 replication (HIC) and a recent study supports a coordinate regulation of ZC3H12A/MCPIP1 and CDKN1A/p21 transcripts in a model of renal carcinoma cells. Here, we explored the potential associations between mRNA expression of ZC3H12A/MCPIP1 and CDKN1A/p21 in HIC sustaining undetectable (elite controllers-EC) or low (viremic controllers-VC) viral loads., Results: We found a selective upregulation of ZC3H12A/MCPIP1 and CDKN1A/p21 mRNA levels in PBMC from HIC compared with both ART-suppressed and HIV-negative control groups (P≤ 0.02) and higher MCPIP1 and p21 proteins levels in HIC than in HIV-1 negative subjects. There was a moderate positive correlation (r ≥ 0.57; P ≤ 0.014) between expressions of both transcripts in HIC and in HIC combined with control groups. We found positive correlations between the mRNA level of CDKN1A/p21 with activated CD4 + T cells levels in HIC (r ≥ 0.53; P ≤ 0.017) and between the mRNA levels of both CDKN1A/p21 (r = 0.74; P = 0.005) and ZC3H12A/MCPIP1 (r = 0.58; P = 0.040) with plasmatic levels of sCD14 in EC. Reanalysis of published transcriptomic data confirmed the positive association between ZC3H12A/MCPIP1 and CDKN1A/p21 mRNA levels in CD4 + T cells and monocytes from disparate cohorts of HIC and other HIV-positive control groups., Conclusions: These data show for the first time the simultaneous upregulation of ZC3H12A/MCPIP1 and CDKN1A/p21 transcripts in the setting of natural suppression of HIV-1 replication in vivo and the positive correlation of the expression of these cellular factors in disparate cohorts of HIV-positive individuals. The existence of a common regulatory pathway connecting ZC3H12A/MCPIP1 and CDKN1A/p21 could have a synergistic effect on HIV-1 replication control and pharmacological manipulation of these multifunctional host factors may open novel therapeutic perspectives to prevent HIV-1 replication and disease progression.

Background: Cardiac cell fate specification occurs through progressive steps, and its gene expression regulation features are still being defined. There has been an increasing interest in understanding the coordination between transcription and post-transcriptional regulation during the differentiation processes. Here, we took advantage of the polysome profiling technique to isolate and high-throughput sequence ribosome-free and polysome-bound RNAs during cardiomyogenesis., Results: We showed that polysome-bound RNAs exhibit the cardiomyogenic commitment gene expression and that mesoderm-to-cardiac progenitor stages are strongly regulated. Additionally, we compared ribosome-free and polysome-bound RNAs and found that the post-transcriptional regulation vastly contributes to cardiac phenotype determination, including RNA recruitment to and dissociation from ribosomes. Moreover, we found that protein synthesis is decreased in cardiomyocytes compared to human embryonic stem-cells (hESCs), possibly due to the down-regulation of translation-related genes., Conclusions: Our data provided a powerful tool to investigate genes potentially controlled by post-transcriptional mechanisms during the cardiac differentiation of hESC. This work could prospect fundamental tools to develop new therapy and research approaches.

Background: Sensory proteins react to changing environmental conditions by transducing signals into the cell. These signals are integrated into core proteins that activate downstream target proteins such as transcription factors (TFs). This structure is referred to as a bow tie, and allows cells to respond appropriately to complex environmental conditions. Understanding this cellular processing of information, from sensory proteins (e.g., cell-surface proteins) to target proteins (e.g., TFs) is important, yet for many processes the signaling pathways remain unknown., Results: Here, we present BowTieBuilder for inferring signal transduction pathways from multiple source and target proteins. Given protein-protein interaction (PPI) data signaling pathways are assembled without knowledge of the intermediate signaling proteins while maximizing the overall probability of the pathway. To assess the inference quality, BowTieBuilder and three alternative heuristics are applied to several pathways, and the resulting pathways are compared to reference pathways taken from KEGG. In addition, BowTieBuilder is used to infer a signaling pathway of the innate immune response in humans and a signaling pathway that potentially regulates an underlying gene regulatory network., Conclusion: We show that BowTieBuilder, given multiple source and/or target proteins, infers pathways with satisfactory recall and precision rates and detects the core proteins of each pathway.